Literature DB >> 22195089

A cloud-based simulation architecture for pandemic influenza simulation.

Henrik Eriksson1, Massimiliano Raciti, Maurizio Basile, Alessandro Cunsolo, Anders Fröberg, Ola Leifler, Joakim Ekberg, Toomas Timpka.   

Abstract

High-fidelity simulations of pandemic outbreaks are resource consuming. Cluster-based solutions have been suggested for executing such complex computations. We present a cloud-based simulation architecture that utilizes computing resources both locally available and dynamically rented online. The approach uses the Condor framework for job distribution and management of the Amazon Elastic Computing Cloud (EC2) as well as local resources. The architecture has a web-based user interface that allows users to monitor and control simulation execution. In a benchmark test, the best cost-adjusted performance was recorded for the EC2 H-CPU Medium instance, while a field trial showed that the job configuration had significant influence on the execution time and that the network capacity of the master node could become a bottleneck. We conclude that it is possible to develop a scalable simulation environment that uses cloud-based solutions, while providing an easy-to-use graphical user interface.

Entities:  

Mesh:

Year:  2011        PMID: 22195089      PMCID: PMC3243184     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  10 in total

1.  Assumptions management in simulation of infectious disease outbreaks.

Authors:  Henrik Eriksson; Magnus Morin; Joakim Ekberg; Johan Jenvald; Toomas Timpka
Journal:  AMIA Annu Symp Proc       Date:  2009-11-14

2.  Impact of precautionary behaviors during outbreaks of pandemic influenza: modeling of regional differences.

Authors:  Joakim Ekberg; Henrik Eriksson; Magnus Morin; Einar Holm; Magnus Strömgren; Toomas Timpka
Journal:  AMIA Annu Symp Proc       Date:  2009-11-14

3.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.

Authors:  Erik von Elm; Douglas G Altman; Matthias Egger; Stuart J Pocock; Peter C Gøtzsche; Jan P Vandenbroucke
Journal:  Lancet       Date:  2007-10-20       Impact factor: 79.321

4.  Ontology based modeling of pandemic simulation scenarios.

Authors:  Henrik Eriksson; Magnus Morin; Johan Jenvald; Elin Gursky; Einar Holm; Toomas Timpka
Journal:  Stud Health Technol Inform       Date:  2007

Review 5.  Emergence of viral diseases: mathematical modeling as a tool for infection control, policy and decision making.

Authors:  Derrick Louz; Hans E Bergmans; Birgit P Loos; Rob C Hoeben
Journal:  Crit Rev Microbiol       Date:  2010-08       Impact factor: 7.624

6.  Studies needed to address public health challenges of the 2009 H1N1 influenza pandemic: insights from modeling.

Authors:  Maria D Van Kerkhove; Tommi Asikainen; Niels G Becker; Steven Bjorge; Jean-Claude Desenclos; Thais dos Santos; Christophe Fraser; Gabriel M Leung; Marc Lipsitch; Ira M Longini; Emma S McBryde; Cathy E Roth; David K Shay; Derek J Smith; Jacco Wallinga; Peter J White; Neil M Ferguson; Steven Riley
Journal:  PLoS Med       Date:  2010-06-01       Impact factor: 11.069

7.  A discrete time-space geography for epidemiology: from mixing groups to pockets of local order in pandemic simulations.

Authors:  Einar Holm; Toomas Timpka
Journal:  Stud Health Technol Inform       Date:  2007

8.  Requirements and design of the PROSPER protocol for implementation of information infrastructures supporting pandemic response: a Nominal Group study.

Authors:  Toomas Timpka; Henrik Eriksson; Elin A Gursky; Magnus Strömgren; Einar Holm; Joakim Ekberg; Olle Eriksson; Anders Grimvall; Lars Valter; James M Nyce
Journal:  PLoS One       Date:  2011-03-28       Impact factor: 3.240

9.  Publication guidelines for quality improvement studies in health care: evolution of the SQUIRE project.

Authors:  Frank Davidoff; Paul Batalden; David Stevens; Greg Ogrinc; Susan E Mooney
Journal:  BMJ       Date:  2009-01-19

Review 10.  Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies.

Authors:  Vernon J Lee; David C Lye; Annelies Wilder-Smith
Journal:  BMC Med       Date:  2009-12-10       Impact factor: 8.775

  10 in total
  4 in total

1.  Dynamic Multicore Processing for Pandemic Influenza Simulation.

Authors:  Henrik Eriksson; Toomas Timpka; Armin Spreco; Örjan Dahlström; Magnus Strömgren; Einar Holm
Journal:  AMIA Annu Symp Proc       Date:  2017-02-10

2.  Relevance of workplace social mixing during influenza pandemics: an experimental modelling study of workplace cultures.

Authors:  T Timpka; H Eriksson; E Holm; M Strömgren; J Ekberg; A Spreco; Ö Dahlström
Journal:  Epidemiol Infect       Date:  2016-02-05       Impact factor: 4.434

Review 3.  A scoping review of cloud computing in healthcare.

Authors:  Lena Griebel; Hans-Ulrich Prokosch; Felix Köpcke; Dennis Toddenroth; Jan Christoph; Ines Leb; Igor Engel; Martin Sedlmayr
Journal:  BMC Med Inform Decis Mak       Date:  2015-03-19       Impact factor: 2.796

4.  Bioinformatics on the cloud computing platform Azure.

Authors:  Hugh P Shanahan; Anne M Owen; Andrew P Harrison
Journal:  PLoS One       Date:  2014-07-22       Impact factor: 3.240

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.